A new test to detect ovarian cancer earlier developed by scientists outperforms previous tests, said researchers led by Levanon and Tamar Geiger of Tel Aviv University report and published in the journal Molecular & Cellular Proteomics. They hope it will help screen women who are genetically predisposed to the disease.
Fewer than half of ovarian cancer patients survive until five years after diagnosis. According to the American Cancer Society, this is because only about one-fifth of ovarian cancer cases are detected early, when the chances of successful treatment and recovery are highest. "If we could change this reality by detecting (ovarian cancer) at a curable stage, we could save many lives," said Keren Levanon, a physician-researcher at Chaim Sheba Medical Center in Israel.
They compared samples from women with ovarian cancer having surgery in the course of treatment and from volunteers who had gynecological surgery for reasons unrelated to cancer, such as uterine fibroids or excessive bleeding.
Using proteomics, the researchers compared thousands of proteins in uterine microvesicles from 12 healthy volunteers and 12 cancer patients. Then they used machine learning algorithms to search for patterns that could distinguish between the samples.
"We developed a diagnostic set of nine proteins that distinguishes women with ovarian cancer from healthy women with greater sensitivity and specificity than reported before," Levanon said.
The researchers then tested the set's accuracy in a cohort of 152 women, 37 of whom were known to have ovarian cancer. The test had 70 percent diagnostic sensitivity, meaning that it correctly detected cancer 25 of the 37 study participants who truly had cancer; and 76 percent specificity, meaning that it correctly identified about three out of every four healthy volunteers as healthy. It outperformed previous proteomics-based tests, which had less than 60 percent sensitivity.
The authors propose that their test may be useful for young women whose risk of developing ovarian cancer is known to be high. They also believe that the method of isolating microvesicles from bodily fluids to detect fainter cancer signals shows promise for other difficult-to-detect types of cancer.